Walker, Mark

Genetic studies of body mass index yield new insights for obesity biology

Study, T. L. C., Locke, A. E., The ADIPOGen Consortium, The AGEN-BMI Working Group, The CARDIOGRAMplusC4D Consortium, The CKDGen Consortium, The, G. L. G. C., The, I. C. B. P., The MAGIC Investigators, The MuTHER Consortium, et al. (2015) · Nature

Genetic Associations and EpidemiologyGenetic Mapping and Diversity in Plants and Animals

Cited by 4,534

A Common Variant in the FTO Gene Is Associated with Body Mass Index and Predisposes to Childhood and Adult Obesity

Frayling, T. M., Timpson, N. J., Weedon, M. N., Zeggini, E., Freathy, R. M., Lindgren, C. M., Perry, J. R. B., Elliott, K. S., Lango, H., Rayner, N. W., et al. (2007) · Science

Genetic Associations and EpidemiologyGenetics and Physical Performance

Cited by 4,531

Replication of Genome-Wide Association Signals in UK Samples Reveals Risk Loci for Type 2 Diabetes

Zeggini, E., Weedon, M. N., Lindgren, C. M., Frayling, T. M., Elliott, K. S., Lango, H., Timpson, N. J., Perry, J. R. B., Rayner, N. W., Freathy, R. M., et al. (2007) · Science

Genetic Associations and EpidemiologyDiabetes and associated disorders

Cited by 2,194

Defining the role of common variation in the genomic and biological architecture of adult human height

The Electronic Medical Records and Genomics (eMERGE) Consortium, Wood, A. R., The MIGen Consortium, The PAGE Consortium, Study, T. L. C., Esko, T., Yang, J., Vedantam, S., Pers, T. H., Gustafsson, S., et al. (2014) · Nature Genetics

Genetic Associations and EpidemiologyGenetics and Physical Performance

Cited by 1,853

Twelve type 2 diabetes susceptibility loci identified through large-scale association analysis

The MAGIC investigators, Voight, B. F., The GIANT Consortium, Scott, L. J., Steinthorsdottir, V., Morris, A. P., Dina, C., Welch, R. P., Zeggini, E., Huth, C., et al. (2010) · Nature Genetics

Genetic Associations and EpidemiologyGenetic Mapping and Diversity in Plants and Animals

Cited by 1,761

New genetic loci link adipose and insulin biology to body fat distribution

The ADIPOGen Consortium, Shungin, D., The CARDIOGRAMplusC4D Consortium, The CKDGen Consortium, The GEFOS Consortium, The GENIE Consortium, The, G. L. G. C., The, I. C. B. P., The International Endogene Consortium, Study, T. L. C., et al. (2015) · Nature

Genetic Associations and EpidemiologyAdipokines, Inflammation, and Metabolic Diseases

Cited by 1,580

The genetic architecture of type 2 diabetes

Fuchsberger, C., Flannick, J., Teslovich, T. M., Mahajan, A., Agarwala, V., Gaulton, K. J., Ma, C., Fontanillas, P., Moutsianas, L., McCarthy, D. J., et al. (2016) · Nature

Genetic Associations and EpidemiologyGenetic Mapping and Diversity in Plants and Animals

Cited by 1,051

A saturated map of common genetic variants associated with human height

Yengo, L., Vedantam, S., Marouli, E., Sidorenko, J., Bartell, E., Sakaue, S., Graff, M., Eliasen, A. U., Jiang, Y., Raghavan, S., et al. (2022) · Nature

Genetic Associations and EpidemiologyGenetics and Physical Performance

Cited by 825

Large-Scale Association Studies of Variants in Genes Encoding the Pancreatic β-Cell KATP Channel Subunits Kir6.2 (KCNJ11) and SUR1 (ABCC8) Confirm That the KCNJ11 E23K Variant Is Associated With Type 2 Diabetes

Gloyn, A. L., Weedon, M. N., Owen, K. R., Turner, M. J., Knight, B. A., Hitman, G., Walker, M., Levy, J. C., Sampson, M., Halford, S., et al. (2003) · Diabetes

Pancreatic function and diabetesGenetic Associations and Epidemiology

Cited by 754

Rare and low-frequency coding variants alter human adult height

Marouli, E., Graff, M., Medina-Gomez, C., Lo, K. S., Wood, A. R., Kjaer, T. R., Fine, R. S., Lu, Y., Schurmann, C., Highland, H. M., et al. (2017) · Nature

Genetic Associations and EpidemiologyGenetics and Physical Performance

Cited by 610

Genetic variation near IRS1 associates with reduced adiposity and an impaired metabolic profile

Kilpeläinen, T. O., Zillikens, M. C., Stančákova, A., Finucane, F. M., Ried, J. S., Langenberg, C., Zhang, W., Beckmann, J. S., Luan, J., Vandenput, L., et al. (2011) · Nature Genetics

Genetic Associations and EpidemiologyAdipokines, Inflammation, and Metabolic Diseases

Cited by 335

Genetic evidence that raised sex hormone binding globulin (SHBG) levels reduce the risk of type 2 diabetes

Perry, J. R. B., Weedon, M. N., Langenberg, C., Jackson, A. U., Lyssenko, V., Sparsø, T., Thorleifsson, G., Grallert, H., Ferrucci, L., Maggio, M., et al. (2010) · Human Molecular Genetics

Genetic Associations and EpidemiologyHormonal and reproductive studies

Cited by 217

Insulin resistance, insulin response, and obesity as indicators of metabolic risk

Ferrannini, E., Balkau, B., Coppack, S. W., Dekker, J. M., Mari, A., Nolan, J., Walker, M., Natali, A., & Beck-Nielsen, H. (2007) · The Journal of Clinical Endocrinology & Metabolism

Diabetes, Cardiovascular Risks, and LipoproteinsAdipokines, Inflammation, and Metabolic Diseases

Cited by 193

A Genome-Wide Association Study of IVGTT-Based Measures of First-Phase Insulin Secretion Refines the Underlying Physiology of Type 2 Diabetes Variants

Wood, A. R., Jonsson, A., Jackson, A. U., Wang, N., van Leewen, N., Palmer, N. D., Kobes, S., Deelen, J., Boquete-Vilarino, L., Paananen, J., et al. (2017) · Diabetes

Genetic Associations and EpidemiologyPancreatic function and diabetes

Cited by 117

Discovery of drug-omics associations in type 2 diabetes with generative deep-learning models

Allesøe, R. L., Lundgaard, A. T., Hernández Medina, R., Aguayo-Orozco, A., Johansen, J., Nissen, J. N., Brorsson, C., Mazzoni, G., Niu, L., Biel, J. H., et al. (2023) · Nature Biotechnology

Bioinformatics and Genomic NetworksComputational Drug Discovery Methods

Cited by 111

Predicting and elucidating the etiology of fatty liver disease: a machine learning modeling and validation study in the IMI DIRECT cohorts

Atabaki-Pasdar, N., Ohlsson, M., Viñuela, A., Frau, F., Pomares-Millan, H., Haid, M., Jones, A. G., Thomas, E. L., Koivula, R. W., Kurbasic, A., et al. (2020) · PLOS Medicine

Liver Disease Diagnosis and TreatmentAlcohol Consumption and Health Effects

Cited by 97

Genetic variants associated with glycine metabolism and their role in insulin sensitivity and type 2 diabetes

Xie, W., Wood, A. R., Lyssenko, V., Weedon, M. N., Knowles, J. W., Alkayyali, S., Assimes, T. L., Quertermous, T., Abbasi, F., Paananen, J., et al. (2013) · Diabetes

Genetic Associations and EpidemiologyMetabolomics and Mass Spectrometry Studies

Cited by 83

Carbohydrate counting at meal time followed by a small secondary postprandial bolus injection at 3 hours prevents late hyperglycemia, without hypoglycemia, after a high-carbohydrate, high-fat meal in type 1 diabetes

Campbell, M. D., Walker, M., King, D., Gonzalez, J. T., Allerton, D., Stevenson, E. J., Shaw, J. A., & West, D. J. (2016) · Diabetes Care

Diabetes Management and ResearchDiabetes Treatment and Management

Cited by 32

Does impaired mitochondrial function affect insulin signaling and action in cultured human skeletal muscle cells?

Brown, A. E., Elstner, M., Yeaman, S. J., Turnbull, D. M., & Walker, M. (2008) · American Journal of Physiology-Endocrinology and Metabolism

Metabolism, Diabetes, and CancerMitochondrial Function and Pathology

Cited by 8